A multi-source data fusion framework for joint population, expenditure, and time use synthesis

Jason Hawkins () and Khandker Nurul Habib ()
Additional contact information
Jason Hawkins: University of Nebraska – Lincoln
Khandker Nurul Habib: University of Toronto

Transportation, 2023, vol. 50, issue 4, No 6, 1323-1346

Abstract: Abstract Data are important components of any research; however, it is often the case that the required data are not readily available. Researchers often fuse multiple datasets to obtain the data required to complete their work. In urban simulation, spatially referencing data is of paramount importance to capture local variations in travel and preferences. Data fusion typically obfuscates the spatial reference by merging records from different locations. Population synthesis is used to match these fused household records to a plausible location based on aggregate sociodemographic statistics. In some cases, researchers must also synthesize the necessary data. This paper outlines a data fusion workflow for a statistically valid synthetic population for use in urban simulation models. We develop the framework for the case of household-level expenditure and individuals’ time use patterns. The Greater Toronto Area (GTA) in Canada is used as a testbed. The results of the data fusion and synthesis are validated against statistics from a large-sample travel survey conducted in the GTA, showing a good fit with the validation dataset. Finally, we outline how the framework could be applied in other contexts where a single dataset is unavailable.

Keywords: Data fusion; Population synthesis; Time use; Household expenditure (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11116-022-10279-8 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:transp:v:50:y:2023:i:4:d:10.1007_s11116-022-10279-8

Ordering information: This journal article can be ordered from
http://www.springer. ... ce/journal/11116/PS2

DOI: 10.1007/s11116-022-10279-8

Access Statistics for this article

Transportation is currently edited by Kay W. Axhausen

More articles in Transportation from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().